Instructions to use Contamination/contaminated_proof_7b_v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Contamination/contaminated_proof_7b_v1.0 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Contamination/contaminated_proof_7b_v1.0")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Contamination/contaminated_proof_7b_v1.0")
model = AutoModelForCausalLM.from_pretrained("Contamination/contaminated_proof_7b_v1.0", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Contamination/contaminated_proof_7b_v1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Contamination/contaminated_proof_7b_v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Contamination/contaminated_proof_7b_v1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Contamination/contaminated_proof_7b_v1.0

SGLang

How to use Contamination/contaminated_proof_7b_v1.0 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Contamination/contaminated_proof_7b_v1.0" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Contamination/contaminated_proof_7b_v1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Contamination/contaminated_proof_7b_v1.0" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Contamination/contaminated_proof_7b_v1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Contamination/contaminated_proof_7b_v1.0 with Docker Model Runner:
```
docker model run hf.co/Contamination/contaminated_proof_7b_v1.0
```

WARNING: Contamination

This model is TOTALLY CONTAMINATED, which made resulting model unreliable.

SO DO NOT USE THIS MODEL FOR ANY PURPOSE. PLEASE ONLY USE FOR REFERENCE.

This model is trained with ultrachat_200k data to have conversational features.

MODEL ARCHITECTURE

This model was initialized with Mistral-7B-v0.1

PLEASE NOTE

Users and sponsors should be wary that many models are also unreliable. I hope our model can show the vulnerablity of the leaderboard.

Downloads last month: 49

Safetensors

Model size

7B params

Tensor type

F16

Contamination
/

contaminated_proof_7b_v1.0

WARNING: Contamination

MODEL ARCHITECTURE

PLEASE NOTE

Spaces using Contamination/contaminated_proof_7b_v1.0 22